Modern production planning uses various methods and techniques to determine when and how much of certain products are to be produced in order to satisfy customer demand while optimally using available resources, available inventories, and available time. Typically, a production plant, through a regularly scheduled process, would determine a plant production schedule for a certain time frame based on plant capacity, current customer orders, and forecast demands. Knowing expected delivery dates is often important for customers, so production plans typically detail rigid production schedules and shipment dates.
It is common, in many industries that rely on production plants, for customers to wish to change their orders. Customers may wish to change the product type ordered, quantity ordered, or delivery date requested in order to fulfill their own obligations. Such changes are typically considered the next time the plant production schedule is evaluated. In some cases, the plant may be able to accommodate such a change with little to no problems. However, in many cases, when a change requested is too large or too close to the final production date, a plant is simply unable to accommodate the customer's wishes and either the customer or the plant will be financially damaged as a result.
In some solutions, such as that described in U.S. Pat. No. 6,393,332, a planning system will attempt to schedule new customer orders in a fashion that uses the plant capacity closest to the required completion date so as to use less of the near-term plant capacity. In these solutions, the plant is able to accommodate more last-minute changes because the last-minute resources are assigned last. However, such planning systems are prone to plant underutilization because established orders become locked into the fulfillment plan without a chance to be reevaluated and repositioned along the production timeframe.
In solutions where the existing orders are reevaluated in determining whether or not a plant can accommodate a demand change, order competition may arise between the existing and updated orders. As customer orders compete for production resources, new or updated orders for one customer can lead to rescheduling of other customers' orders, even ones with previously confirmed production or shipping dates. As a result, production plants managers are placed in a position where they must weigh the costs and benefits of either accepting the requested changes to their production schedule or maintaining the commitments of the current customer demands already established in the production schedule.
Customer demand changes can therefore result in high organizational and administrative costs. Also, such demand changes may force the production plant to miss established deadlines, thus leading to a decline in customer satisfaction. Either situation leads to missed revenue growth opportunities or possible revenue loss. Any unreliable lead times deprive customers of a reliable planning base for their own operations and increase variability in the supply chain, which can lead to a need for large, inefficient safety stocks.
Some current solutions that overcome these drawbacks use a “frozen zone” time period in their production plans. During the “frozen zone” time period, which usually extends for a period of several days or weeks prior to the delivery date depending on the production complexity, no changes in a customer's order are allowed. This approach, while alleviating the difficult change-or-stay decision dilemma of the manager in charge of production planning, takes out any short-term flexibility once available in the ordering and production process. A customer is then locked into an order after a certain date even if the customer's needs drastically change. This problem is exacerbated in industries with short life-cycle products. This restriction on ordering freedom can cause customers to shop around for a production plant with a shorter “frozen zone” time period which may only be offered by a small number of production plants with large enough safety assets.
Another solution to the change-or-stay decision dilemma is used in some production plants where customers or distribution channels are assigned different importance levels. In some of these plants, the production schedules allocate a limited product supply or limited resources to minor accounts in order to ensure order fulfillment for key accounts. While this solution fixes allocation of supply, it reduces the flexibility available for producers or consumers to follow market demand. This reduced flexibility again jeopardizes revenue opportunities.
Additionally, many current solutions, including U.S. Pat. No. 6,393,332, use complicated algorithms and systems that take longer to run and analyze and require specialized systems and implementations that can greatly increase start-up costs. As a result, there is a current need for a fulfillment planning system which can operate with more efficiency and economy. This need is felt more in smaller and younger operations in need of a fulfillment planning system.
Many current solutions, such as U.S. Pat. No. 7,295,990, attempt to solve fulfillment planning solutions by forecasting ahead in an attempt to guess future demand. While this technique has its benefits, there are also numerous risks inherently involved in forecasting which make such systems unusable in certain fields. As a result, there is a current need for a fulfillment planning system which is capable of creating an accurate and efficient fulfillment plan without relying on estimated and forecast data. This need is especially prevalent in risk-adverse fulfillment operations that are unable to accommodate excessive safety stocks or unfulfilled orders.
There is a current need for a fulfillment planning system which, among other benefits, provides: Reliability of production plans for customers; Steadiness of production plans; Supply and production flexibility in terms of both quantity and time, and; Alignment of marketing and sales strategy with supply. There is also a current need for a fulfillment planning system which can accomplish these goals efficiently and economically.